MU-MIMO Antenna Subpanel Partitioning for Lower Complexity
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Solution Overview
Problem
The increasing computational complexity and energy consumption challenges posed by high-order MU-MIMO systems, particularly in 5G-advanced and 6G base stations, necessitate a more efficient approach for managing large antenna panels and user equipment groups.
Innovation Solution
The method involves logically partitioning an antenna panel into multiple subpanels and assigning user groups for MU-MIMO spatial multiplexing, with each group served by a dedicated subpanel, reducing computational complexity and enhancing energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-order MU-MIMO is implemented to increase spectral efficiency and beamforming gain, then system performance is improved, but computational complexity increases significantly
Solution Approach 1:
The antenna panel is divided into multiple subpanels, and users are grouped into separate user groups, with each user group served by a dedicated subpanel. This segmentation reduces the computational complexity of channel estimation and precoding operations by breaking down the large-scale MIMO problem into smaller, independent subproblems.
2Productivity
If high-order MU-MIMO is implemented to increase spectral efficiency, then system capacity is improved, but energy consumption increases
Solution Approach 1:
By dividing the antenna panel into subpanels and assigning each user group to a specific subpanel, the system reduces the number of computations required for channel estimation and precoding, thereby lowering energy consumption while maintaining high spectral efficiency through multi-user spatial multiplexing.
3Power
If a large antenna panel is used to support high-order MU-MIMO, then beamforming gain is improved, but device complexity increases
Solution Approach 1:
The large antenna panel is segmented into multiple subpanels, each serving a specific user group. This reduces the complexity of managing and processing signals from a large number of antennas while maintaining beamforming gain through dedicated subpanel-to-user-group assignments.
Solution Approach 2:
Each subpanel is optimized to serve a specific user group with tailored beamforming parameters, allowing local optimization of beamforming gain for each user group while reducing overall system complexity through modular management of subpanels.
Data Source
AI summary
A method includes logically partitioning an antenna panel of a base station into multiple subpanels. The method also includes identifying multiple user groups for multi-user multiple-input multiple-output (MU-MIMO) spatial multiplexing, each user group comprising one or more user equipments (UEs). The method also includes assigning the user groups to the subpanels. The method also includes transmitting to the UEs via the subpanels, wherein each user group is served by one subpanel of the multiple subpanels.


